Triple

T19273676
Position Surface form Disambiguated ID Type / Status
Subject Zubeidaa E481991 entity
Predicate castMember P1668 FINISHED
Object Karisma Kapoor NE NERFINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Karisma Kapoor | Statement: [Zubeidaa, castMember, Karisma Kapoor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Karisma Kapoor
Context triple: [Zubeidaa, castMember, Karisma Kapoor]
  • A. Karisma Kapoor chosen
    Karisma Kapoor is an acclaimed Indian film actress best known for her leading roles in popular Hindi movies of the 1990s and early 2000s.
  • B. Madhuri Dixit
    Madhuri Dixit is a celebrated Indian actress and dancer, renowned for her leading roles in Hindi cinema since the late 1980s and widely regarded as one of Bollywood’s most iconic stars.
  • C. Raveena Tandon
    Raveena Tandon is an Indian actress and producer known for her prominent roles in 1990s and early 2000s Bollywood films and for winning the National Film Award for Best Actress.
  • D. Kajol
    Kajol is a renowned Indian film actress celebrated for her powerful performances and iconic roles in Hindi cinema since the 1990s.
  • E. Seema Kapoor
    Seema Kapoor is an Indian television and film actress and director, known for her work in Hindi entertainment and her marriage to the late actor Om Puri.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d8e8ce54cc8190998418ff1f66ef28 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5fbba7758819081c1c78667c59c5e completed April 20, 2026, 10:11 a.m.
Created at: April 10, 2026, 1:29 p.m.